Constructive contrasts between modeled and measured climate responses overa regional scale

Reducing uncertainty in predictions of regional-scale models depends on mea ningful contrasts with field measurements. This paper introduces a two-stag e process that works from the premise that an appropriate goal for regional models is to produce reasonable behavior over dominant environmental gradi ents. We demonstrate two techniques for contrasting models with data, one b ased on the shape of modeled relationships (functional contrasts) and the o ther based on an examination of the residuals (residual contrasts) between the model and an empirically derived surface fit to field data. Functional contrasts evaluated the differences between the response of simulated net p rimary production (NPP) to climate variables and the response observed in f ield measurements of NPP. Residual contrasts compared deviations of NPP fro m the empirical surface to identify groupings (for example, vegetation clas ses, geographic regions) with model deviations different from those of the field data. In all model-data contrasts, we assigned sample weights to fiel d measurements to ensure unbiased representation of the region, and we incl uded both constructive comparisons and formal statistical tests. In general , we learned more from constructive methods designed to reveal structure or pattern in discrepancy than we did from statistical tests designed to fals ify models. Although our constructive methods were more subjective and less concise, they succeeded in revealing gaps in our understanding of regional -scale processes that can guide future efforts to reduce scientific uncerta inty. This was best illustrated by NPP predictions from the Biome-BGC model , which showed a stronger response to precipitation than apparently operate s in the field. In another case, differences revealed in savanna and dry wo odlands had insufficient field-data support, suggesting a need for future f ield studies to improve understanding in this, and other, poorly studied ec osystems.